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/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.hadoop.hive.ql.exec.tez;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Set;
import java.util.TreeMap;
import org.apache.hadoop.hive.llap.LlapUtil;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.apache.hadoop.hive.conf.HiveConf;
import org.apache.hadoop.hive.ql.exec.DummyStoreOperator;
import org.apache.hadoop.hive.ql.exec.HashTableDummyOperator;
import org.apache.hadoop.hive.ql.exec.MapredContext;
import org.apache.hadoop.hive.ql.exec.ObjectCache;
import org.apache.hadoop.hive.ql.exec.ObjectCacheFactory;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.OperatorUtils;
import org.apache.hadoop.hive.ql.exec.Utilities;
import org.apache.hadoop.hive.ql.exec.mr.ExecMapper.ReportStats;
import org.apache.hadoop.hive.ql.exec.tez.DynamicValueRegistryTez.RegistryConfTez;
import org.apache.hadoop.hive.ql.exec.tez.TezProcessor.TezKVOutputCollector;
import org.apache.hadoop.hive.ql.log.PerfLogger;
import org.apache.hadoop.hive.ql.plan.BaseWork;
import org.apache.hadoop.hive.ql.plan.DynamicValue;
import org.apache.hadoop.hive.ql.plan.ReduceWork;
import org.apache.hadoop.hive.ql.plan.TableDesc;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.mapred.JobConf;
import org.apache.tez.mapreduce.processor.MRTaskReporter;
import org.apache.tez.runtime.api.Input;
import org.apache.tez.runtime.api.LogicalInput;
import org.apache.tez.runtime.api.LogicalOutput;
import org.apache.tez.runtime.api.ProcessorContext;
import org.apache.tez.runtime.api.Reader;
import com.google.common.collect.Lists;
/**
* Process input from tez LogicalInput and write output - for a map plan
* Just pump the records through the query plan.
*/
public class ReduceRecordProcessor extends RecordProcessor {
private static final Logger LOG = LoggerFactory.getLogger(ReduceRecordProcessor.class);
private static final String REDUCE_PLAN_KEY = "__REDUCE_PLAN__";
private final ObjectCache cache, dynamicValueCache;
private ReduceWork reduceWork;
private final List mergeWorkList;
private final List cacheKeys;
private final List dynamicValueCacheKeys = new ArrayList<>();
private final Map connectOps = new TreeMap<>();
private final Map tagToReducerMap = new HashMap<>();
private Operator reducer;
private ReduceRecordSource[] sources;
private byte bigTablePosition = 0;
public ReduceRecordProcessor(final JobConf jconf, final ProcessorContext context) throws Exception {
super(jconf, context);
String queryId = HiveConf.getVar(jconf, HiveConf.ConfVars.HIVEQUERYID);
cache = ObjectCacheFactory.getCache(jconf, queryId, true);
dynamicValueCache = ObjectCacheFactory.getCache(jconf, queryId, false, true);
String cacheKey = processorContext.getTaskVertexName() + REDUCE_PLAN_KEY;
cacheKeys = Lists.newArrayList(cacheKey);
reduceWork = cache.retrieve(cacheKey, () -> Utilities.getReduceWork(jconf));
Utilities.setReduceWork(jconf, reduceWork);
mergeWorkList = getMergeWorkList(jconf, cacheKey, queryId, cache, cacheKeys);
}
@Override
void init(MRTaskReporter mrReporter, Map inputs, Map outputs)
throws Exception {
perfLogger.perfLogBegin(CLASS_NAME, PerfLogger.TEZ_INIT_OPERATORS);
super.init(mrReporter, inputs, outputs);
MapredContext.init(false, new JobConf(jconf));
List shuffleInputs = getShuffleInputs(inputs);
// TODO HIVE-14042. Move to using a loop and a timed wait once TEZ-3302 is fixed.
checkAbortCondition();
if (shuffleInputs != null) {
LOG.info("Waiting for ShuffleInputs to become ready");
processorContext.waitForAllInputsReady(new ArrayList(shuffleInputs));
}
connectOps.clear();
ReduceWork redWork = reduceWork;
LOG.info("Main work is " + reduceWork.getName());
List workOps = reduceWork.getDummyOps();
Set dummyOps = workOps == null ? new HashSet<>() : new HashSet<>(workOps);
tagToReducerMap.put(redWork.getTag(), redWork);
if (mergeWorkList != null) {
for (BaseWork mergeWork : mergeWorkList) {
LOG.debug("Additional work {}", mergeWork.getName());
workOps = mergeWork.getDummyOps();
if (workOps != null) {
dummyOps.addAll(workOps);
}
ReduceWork mergeReduceWork = (ReduceWork) mergeWork;
reducer = mergeReduceWork.getReducer();
// Check immediately after reducer is assigned, in cae the abort came in during
checkAbortCondition();
DummyStoreOperator dummyStoreOp = getJoinParentOp(reducer);
connectOps.put(mergeReduceWork.getTag(), dummyStoreOp);
tagToReducerMap.put(mergeReduceWork.getTag(), mergeReduceWork);
}
((TezContext) MapredContext.get()).setDummyOpsMap(connectOps);
}
checkAbortCondition();
bigTablePosition = (byte) reduceWork.getTag();
ObjectInspector[] mainWorkOIs = null;
((TezContext) MapredContext.get()).setInputs(inputs);
((TezContext) MapredContext.get()).setTezProcessorContext(processorContext);
int numTags = reduceWork.getTagToValueDesc().size();
reducer = reduceWork.getReducer();
// Check immediately after reducer is assigned, in cae the abort came in during
checkAbortCondition();
// set memory available for operators
long memoryAvailableToTask = processorContext.getTotalMemoryAvailableToTask();
if (reducer.getConf() != null) {
reducer.getConf().setMaxMemoryAvailable(memoryAvailableToTask);
LOG.info("Memory available for operators set to {}", LlapUtil.humanReadableByteCount(memoryAvailableToTask));
}
OperatorUtils.setMemoryAvailable(reducer.getChildOperators(), memoryAvailableToTask);
// Setup values registry
String valueRegistryKey = DynamicValue.DYNAMIC_VALUE_REGISTRY_CACHE_KEY;
DynamicValueRegistryTez registryTez =
dynamicValueCache.retrieve(valueRegistryKey, () -> new DynamicValueRegistryTez());
dynamicValueCacheKeys.add(valueRegistryKey);
RegistryConfTez registryConf = new RegistryConfTez(jconf, reduceWork, processorContext, inputs);
registryTez.init(registryConf);
checkAbortCondition();
if (numTags > 1) {
sources = new ReduceRecordSource[numTags];
mainWorkOIs = new ObjectInspector[numTags];
initializeMultipleSources(reduceWork, numTags, mainWorkOIs, sources);
((TezContext) MapredContext.get()).setRecordSources(sources);
reducer.initialize(jconf, mainWorkOIs);
} else {
numTags = tagToReducerMap.keySet().size();
sources = new ReduceRecordSource[numTags];
mainWorkOIs = new ObjectInspector[numTags];
for (int i : tagToReducerMap.keySet()) {
redWork = tagToReducerMap.get(i);
reducer = redWork.getReducer();
// Check immediately after reducer is assigned, in cae the abort came in during
checkAbortCondition();
initializeSourceForTag(redWork, i, mainWorkOIs, sources, redWork.getTagToValueDesc().get(0),
redWork.getTagToInput().get(0));
reducer.initializeLocalWork(jconf);
}
reducer = reduceWork.getReducer();
// Check immediately after reducer is assigned, in cae the abort came in during
checkAbortCondition();
((TezContext) MapredContext.get()).setRecordSources(sources);
reducer.initialize(jconf, new ObjectInspector[] {mainWorkOIs[bigTablePosition]});
for (int i : tagToReducerMap.keySet()) {
if (i == bigTablePosition) {
continue;
}
redWork = tagToReducerMap.get(i);
reducer = redWork.getReducer();
// Check immediately after reducer is assigned, in cae the abort came in during
checkAbortCondition();
reducer.initialize(jconf, new ObjectInspector[] {mainWorkOIs[i]});
}
}
checkAbortCondition();
reducer = reduceWork.getReducer();
// initialize reduce operator tree
try {
LOG.info(reducer.dump(0));
// Initialization isn't finished until all parents of all operators
// are initialized. For broadcast joins that means initializing the
// dummy parent operators as well.
for (HashTableDummyOperator dummyOp : dummyOps) {
// TODO HIVE-14042. Propagating abort to dummyOps.
dummyOp.initialize(jconf, null);
checkAbortCondition();
}
// set output collector for any reduce sink operators in the pipeline.
List> children = new ArrayList<>();
children.add(reducer);
children.addAll(dummyOps);
createOutputMap();
OperatorUtils.setChildrenCollector(children, outMap);
checkAbortCondition();
reducer.setReporter(reporter);
MapredContext.get().setReporter(reporter);
} catch (Throwable e) {
super.setAborted(true);
if (e instanceof OutOfMemoryError) {
// Don't create a new object if we are already out of memory
throw (OutOfMemoryError) e;
} else if (e instanceof InterruptedException) {
LOG.info("Hit an interrupt while initializing ReduceRecordProcessor. Message={}", e.getMessage());
throw (InterruptedException) e;
} else {
throw new RuntimeException(redWork.getName() + " operator initialization failed", e);
}
}
perfLogger.perfLogEnd(CLASS_NAME, PerfLogger.TEZ_INIT_OPERATORS);
}
private void initializeMultipleSources(ReduceWork redWork, int numTags, ObjectInspector[] ois,
ReduceRecordSource[] sources) throws Exception {
for (int tag = 0; tag < redWork.getTagToValueDesc().size(); tag++) {
if (redWork.getTagToValueDesc().get(tag) == null) {
continue;
}
checkAbortCondition();
initializeSourceForTag(redWork, tag, ois, sources, redWork.getTagToValueDesc().get(tag),
redWork.getTagToInput().get(tag));
}
}
private void initializeSourceForTag(ReduceWork redWork, int tag, ObjectInspector[] ois, ReduceRecordSource[] sources,
TableDesc valueTableDesc, String inputName) throws Exception {
reducer = redWork.getReducer();
reducer.getParentOperators().clear();
reducer.setParentOperators(null); // clear out any parents as reducer is the root
TableDesc keyTableDesc = redWork.getKeyDesc();
Reader reader = inputs.get(inputName).getReader();
sources[tag] = new ReduceRecordSource();
// Only the big table input source should be vectorized (if applicable)
// Note this behavior may have to change if we ever implement a vectorized merge join
boolean vectorizedRecordSource = (tag == bigTablePosition) && redWork.getVectorMode();
sources[tag].init(jconf, redWork.getReducer(), vectorizedRecordSource, keyTableDesc, valueTableDesc, reader,
tag == bigTablePosition, (byte) tag, redWork.getVectorizedRowBatchCtx(), redWork.getVectorizedVertexNum(),
redWork.getVectorizedTestingReducerBatchSize());
ois[tag] = sources[tag].getObjectInspector();
}
@Override
void run() throws Exception {
for (Entry outputEntry : outputs.entrySet()) {
LOG.info("Starting Output: " + outputEntry.getKey());
if (!isAborted()) {
outputEntry.getValue().start();
((TezKVOutputCollector) outMap.get(outputEntry.getKey())).initialize();
}
}
// run the operator pipeline
startAbortChecks();
while (sources[bigTablePosition].pushRecord()) {
addRowAndMaybeCheckAbort();
}
}
@Override
public void abort() {
// this will stop run() from pushing records, along with potentially
// blocking initialization.
super.abort();
if (reducer != null) {
LOG.info("Forwarding abort to reducer: {} " + reducer.getName());
reducer.abort();
} else {
LOG.info("reducer not setup yet. abort not being forwarded");
}
}
/**
* Get the inputs that should be streamed through reduce plan.
*
* @param inputs
* @return
* @throws Exception
*/
private List getShuffleInputs(Map inputs) throws Exception {
// the reduce plan inputs have tags, add all inputs that have tags
Map tagToinput = reduceWork.getTagToInput();
ArrayList shuffleInputs = new ArrayList();
for (String inpStr : tagToinput.values()) {
if (inputs.get(inpStr) == null) {
throw new AssertionError("Cound not find input: " + inpStr);
}
inputs.get(inpStr).start();
shuffleInputs.add(inputs.get(inpStr));
}
return shuffleInputs;
}
@Override
void close() {
if (cache != null) {
for (String key : cacheKeys) {
cache.release(key);
}
}
if (dynamicValueCache != null) {
for (String k : dynamicValueCacheKeys) {
dynamicValueCache.release(k);
}
}
try {
if (isAborted()) {
for (ReduceRecordSource rs : sources) {
if (!rs.close()) {
setAborted(false); // Preserving the old logic. Hmm...
break;
}
}
}
boolean abort = isAborted();
reducer.close(abort);
if (mergeWorkList != null) {
for (BaseWork redWork : mergeWorkList) {
((ReduceWork) redWork).getReducer().close(abort);
}
}
// Need to close the dummyOps as well. The operator pipeline
// is not considered "closed/done" unless all operators are
// done. For broadcast joins that includes the dummy parents.
List dummyOps = reduceWork.getDummyOps();
if (dummyOps != null) {
for (Operator dummyOp : dummyOps) {
dummyOp.close(abort);
}
}
ReportStats rps = new ReportStats(reporter, jconf);
reducer.preorderMap(rps);
} catch (Exception e) {
if (!isAborted()) {
// signal new failure to map-reduce
LOG.error("Hit error while closing operators - failing tree");
throw new RuntimeException("Hive Runtime Error while closing operators: " + e.getMessage(), e);
}
} finally {
Utilities.clearWorkMap(jconf);
MapredContext.close();
}
}
private DummyStoreOperator getJoinParentOp(Operator mergeReduceOp) {
for (Operator childOp : mergeReduceOp.getChildOperators()) {
if ((childOp.getChildOperators() == null) || (childOp.getChildOperators().isEmpty())) {
if (childOp instanceof DummyStoreOperator) {
return (DummyStoreOperator) childOp;
} else {
throw new IllegalStateException("Was expecting dummy store operator but found: " + childOp);
}
} else {
return getJoinParentOp(childOp);
}
}
throw new IllegalStateException("Expecting a DummyStoreOperator found op: " + mergeReduceOp);
}
}
